Millimeter wave (mmWave) cellular systems have been proposed to accommodate the explosive trends in mobile data demands due to the availability of large bands of spectrum. Millimeter wave's high carrier frequency facilitates packing many antenna elements in small form factors, thus enabling multiple-input multiple-output (MIMO) processing with very large arrays. The concept of massive MIMO is believed to play a key role in future wireless systems.
Precoding in mmWave systems with large arrays is needed to counteract high path loss with highly directional transmission. Prior mmWave precoding strategies, however, have made very limited use of MIMO signal processing results for a variety of reasons. For example, MIMO often assumes hardware complexity that is impractical in large arrays, such as a dedicated radio frequency (RF) chain per antenna element. This architecture places constant modulus constraints on precoder designs.
To address this problem, antenna selection and equal gain transmission have been proposed. Antenna selection, however, does not fully utilize the spectral efficiency offered by large antenna arrays, and even more is not designed to provide multiplexing gain. While equal gain transmission generally performs better than antenna selection, it fails to approach the maximum data rate possible in the system. In the case of single stream beamforming, equal gain beamforming solutions are limited to iterative algorithms that are not guaranteed to converge to a globally optimum solution. Therefore, there are very limited MIMO precoding designs that allow systems to approach capacity while satisfying the hardware constraints present in a millimeter wave transceiver.
Moreover, precoding design and analysis, such as equal gain transmission, often assumes idealized fading environments, such as Rayleigh fading. However, scattering is limited by the large pathloss in mmWave systems. Moreover, the richness of scattering in the wireless channel does not scale with antenna array size. This makes idealized fading unrealistically rich, especially when very large tightly packed arrays are considered. Realistic models, such as clustered channel models, have been proposed, though they are seldom used in precoder design. This outlines yet another shortcoming of existing precoding solutions, which is the lack of structure in the precoders. When the channel structure is neglected by assuming distributions like Rayleigh, equal gain precoders or optimal singular value decomposition solutions (which are too complex to implement in hardware) have a uniform distribution over the large feasible set. This uniform distribution means that a lot of information needs to be fed back to the transmitter in order to perform precoding. In general, the number of free variables that needs to be fed back scales with the number of transmit antennas. When the number of transmit antennas is on the order of tens or hundreds, as is the case in millimeter wave systems, this amount of feedback can incur prohibitively large overhead.
Accordingly, there is a need for methods, apparatuses, and systems that address one or more of the above-described issues.